Title:
COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis

Abstract: At the time of writing, the world population is suffering from more than
10,000 registered COVID-19 disease epidemic induced deaths since the outbreak
of the Corona virus more than three months ago now officially known as
SARS-CoV-2. Since, tremendous efforts have been made worldwide to counter-steer
and control the epidemic by now labelled as pandemic. In this contribution, we
provide an overview on the potential for computer audition (CA), i.e., the
usage of speech and sound analysis by artificial intelligence to help in this
scenario. We first survey which types of related or contextually significant
phenomena can be automatically assessed from speech or sound. These include the
automatic recognition and monitoring of breathing, dry and wet coughing or
sneezing sounds, speech under cold, eating behaviour, sleepiness, or pain to
name but a few. Then, we consider potential use-cases for exploitation. These
include risk assessment and diagnosis based on symptom histograms and their
development over time, as well as monitoring of spread, social distancing and
its effects, treatment and recovery, and patient wellbeing. We quickly guide
further through challenges that need to be faced for real-life usage. We come
to the conclusion that CA appears ready for implementation of (pre-)diagnosis
and monitoring tools, and more generally provides rich and significant, yet so
far untapped potential in the fight against COVID-19 spread.